Systems and methods to aggregate loads for demand response events

ABSTRACT

A method includes receiving at least one event parameter for a demand response event and identifying a pool of customers. The pool of customers includes a plurality of customers potentially usable to support the demand response event. Characteristics of each customer in the pool of customers are retrieved and a plurality of groups of customers are created from the pool of customers based on the retrieved characteristics and the at least one event parameter.

BACKGROUND OF THE INVENTION

The field of the invention relates generally to demand response systemsand, more particularly, to a computing device for use with a demandresponse system that enables dynamic aggregation of resources forscheduling demand response events.

The combination of the increasing world population and the increased useof electric vehicles has created an increased electricity energy demand.Energy demand has also increased for use to power buildings, homes,and/or to charge batteries or other energy sources used in electricvehicles. The demand on the power grid has increased as the cost of fuelhas increased. Such demands will likely cause an increase in the priceof energy from the power grid. In particular, initially at least, theprice of energy is likely to increase during peak times of high demand.

Currently, at least some known utilities use demand response systemsthat enable customers to enroll in at least one demand response programto manage the consumption of energy by their customers in response tosupply conditions. Examples of demand response programs include a directcontrol program, a critical peak pricing program, and a time of useprogram. The initiation and/or implementation of a demand responseprogram by a utility is known as a demand response event. A demandresponse event is initiated by a utility transmitting a plurality ofsignals to its customers. For example, a demand response eventrepresentative of a direct load control program, is initiated when theutility transmits a signal to a device within a building, such as anin-home smart device and/or smart thermostat, such that the utility isenabled to directly control the usage of energy consuming machineswithin the building. A demand response event representative of acritical peak pricing program occurs when the utility transmits pricingsignals to its customers during peak demand times. The pricing signalsenable the utility to apprise customers of heightened energy pricesduring peak demand time periods such that customers may limit theirenergy consumption during such peak demand time periods. A demandresponse event representative of a time of use program occurs when theutility transmits a signal to a customer that is representative ofenergy prices that correspond to a time range such that the customer mayidentify an optimal time of day and/or day of the week to consume energyto ensure a low energy price rate.

Such demand response systems enable the utility to manage peak loadconditions and to reduce energy demand among their customers. However,current demand response systems typically group customers in staticgroups by physical location on the grid and/or by the demand reserveprogram in which the customers participate. Current demand responsesystems also transmit a large number of signals to customers during ademand response event and the signals are transmitted at the same timeto all the customers. These characteristics can result in variousproblems, such as load spiking and phase imbalance.

BRIEF DESCRIPTION OF THE INVENTION

In one embodiment, a computing device for use with a demand responsesystem is provided. The computing device includes a memory device forstoring customer data of a plurality of customers of a utility and aprocessor coupled to the memory device. The processor is programmed toreceive at least one event parameter for a demand response event andidentify a pool of customers from the plurality of customers of theutility. The pool of customers includes a plurality of customerspotentially usable to support the demand response event. The processoris programmed to retrieve characteristics of each customer in the poolof customers; and create a plurality of groups of customers from thepool of customers based on the retrieved characteristics and the atleast one event parameter.

In another embodiment, a demand response system is provided. The demandresponse system includes a computing device. The computing deviceincludes a memory device for storing customer data of a plurality ofcustomers of a utility and a processor coupled to the memory device. Theprocessor is programmed to receive at least one event parameter for ademand response event and identify a pool of customers from theplurality of customers of the utility. The pool of customers includes aplurality of customers potentially usable to support the demand responseevent. The processor is programmed to retrieve characteristics of eachcustomer in the pool of customers; and create a plurality of groups ofcustomers from the pool of customers based on the retrievedcharacteristics and the at least one parameter.

In yet another embodiment, a method for providing demand response eventsis provided. The method includes receiving at least one event parameterfor a demand response event and identifying a pool of customers. Thepool of customers includes a plurality of customers potentially usableto support the demand response event. The method includes retrievingcharacteristics of each customer in the pool of customers and creating aplurality of groups of customers from the pool of customers based on theretrieved characteristics and the at least one event parameter.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of an exemplary demand response system;

FIG. 2 is another block diagram of the demand response system shown inFIG. 1;

FIG. 3 is a block diagram of an exemplary computing device that may beused with the demand response system shown in FIGS. 1 and 2; and

FIG. 4 is a flow chart of an exemplary method that may be used forproviding demand response events using the computing device shown inFIG. 3.

DETAILED DESCRIPTION OF THE INVENTION

The exemplary systems and methods described herein overcome at leastsome known disadvantages of known demand response systems by enabling autility to selectively transmit signals representative of demandresponse programs to customers. More specifically, the embodimentsdescribed herein provide a computing device for use with a demandresponse system. The computing device includes a memory device forstoring customer data of a plurality of customers of a utility and aprocessor coupled to said memory device. The processor is programmed toreceive at least one event parameter for a demand response event,identify a pool of customers from the plurality of customers of theutility, retrieve characteristics of each customer in the pool ofcustomers, and create a plurality of groups of customers from the poolof customers based on the retrieved characteristics and the at least oneparameter. The pool of customers includes a plurality of customerspotentially usable to support the demand response event. By dynamicallyselecting groups of customers based on retrieved characteristics of thecustomers and at least one event parameter, as opposed to using staticgroups of customers based on location or demand response program, theutility is able to target specific customers, grid locations, powerconsuming devices, and/or electric phases, to reduce the chances for afailure of the grid, reduce power spikes on the grid, and/or balanceload distribution.

FIGS. 1 and 2 illustrate a demand response system 100. In the exemplaryembodiment, demand response system 100 includes a utility 102. Utility102 includes an electric power generation system 104 and a computingdevice 106. Computing device 106 enables utility 102 to communicate withcustomers and electric power generation system 104 supplies electricalpower to customers via an electric network 108 (shown in FIG. 2).Electric power generation system 104 may include a generator driven by,for example, a gas turbine engine, a hydroelectric turbine, a windturbine, one or more solar panels, and/or another suitable generationsystem. In other embodiments, electric power generation system 104 maybe positioned at a different location from computing device 106 and/orcomputing device 106 may not be positioned within utility 102 and may bepositioned external to utility 102.

In the exemplary embodiment, computing device 106 is communicativelycoupled to a plurality of buildings 110, which may be occupied by aplurality of customers. It should be noted that, as used herein, theterm “couple” is not limited to a direct mechanical, electrical, and/orcommunication connection between components, but may also include anindirect mechanical, electrical, and/or communication connection betweenmultiple components.

In the exemplary embodiment, electric power generation system 104 iscoupled to buildings 110 via electric network 108 to provide power tobuildings 110. More specifically, each building includes one or morepower consuming devices 112, which may utilize power provided byelectric power generation system 104. While power consuming devices 112may be any type of device that consumes electrical power, in theexemplary embodiment, power consuming devices 112 may include anelectric water heater 114, an air conditioner 116, and/or a pool pump118. For purposes of this embodiment, power consuming devices 112 ofeach illustrated building 110 include one or more of electric waterheater 114, air conditioner 116, and/or pool pump 118. In someembodiments, at least one building 110 may not include any of electricwater heater 114, air conditioner 116, and pool pump 118.

In the illustrated embodiment, electric network 108 includes a firstlateral line 120 and a second lateral line 122. Each lateral lineincludes a plurality of transformers 124 (sometimes referred to as poletop transformers). At least one building 110 is coupled to electricnetwork 108 via each transformer 124. First and second lateral lines 120and 122 are connected at a node 126, which may be a substation, atransformer, a switch, etc. For simplicity, a single line diagram isillustrated for electric network 108. Electric network 108 may, however,include multiple wires carrying multiple phases of electric power andbuildings 110 may be connected to different phases of electric power.

In the exemplary embodiment, computing device 106 is communicativelycoupled to at least one user notification 128 device within eachbuilding 110 via a network 129 (shown in FIG. 1) such that computingdevice 106 may communicate with user notification device 128. In theexemplary embodiment, user notification device 128 may be a computer, acellular phone, and/or a smart device, including a smart box and/orsmart thermostat. Alternatively, user notification device 128 may be anyother device that is configured to communicate with computing device106. Moreover, in the exemplary embodiment, user notification device 128includes a user interface 130 that receives at least one input from auser, such as a customer of utility 102. In other embodiments, usernotification device 128 may not include user interface 130. In theexemplary embodiment, user interface 130 may include, for example, akeyboard, a pointing device, a mouse, a stylus, a touch sensitive panel(e.g., a touch pad or a touch screen), a gyroscope, an accelerometer, aposition detector, and/or an audio input interface (e.g., including amicrophone) that enables the user to input pertinent information.

Moreover, in the exemplary embodiment, user notification device 128includes a presentation interface 132 that presents information, such asinformation regarding demand response programs and/or demand responseevents that are received from utility 102, input events and/orvalidation results, to the user. In the exemplary embodiment,presentation interface 132 includes a display adapter (not shown) thatis coupled to at least one display device (not shown). Morespecifically, in the exemplary embodiment, the display device is avisual display device, such as a cathode ray tube (CRT), a liquidcrystal display (LCD), an organic LED (OLED) display, and/or an“electronic ink” display. Alternatively, presentation interface 132 mayinclude an audio output device (e.g., an audio adapter and/or a speaker)and/or a printer. In other embodiments, user notification device 128 maynot include presentation interface 132.

In the exemplary embodiment, computing device 106 may communicate withuser notification device 128 using a wired network connection (e.g.,Ethernet or an optical fiber), a wireless communication means, such asradio frequency (RF), e.g., FM radio and/or digital audio broadcasting,an Institute of Electrical and Electronics Engineers (IEEE®) 802.11standard (e.g., 802.11(g) or 802.11(n)), the Worldwide Interoperabilityfor Microwave Access (WIMAX®) standard, cellular phone technology (e.g.,the Global Standard for Mobile communication (GSM)), a satellitecommunication link, and/or any other suitable communication means. Morespecifically, in the exemplary embodiment, user notification device 128is configured to receive at least one signal from computing device 106that is representative of at least one demand response event. In theexemplary embodiment, the demand response event initiates theimplementation of a demand response program that may include a directload control program, a critical peak pricing program, and/or a time ofuse program.

In the exemplary embodiment, utility 102 also includes a data managementsystem 134 that is coupled to computing device 106 via network 129. Datamanagement system 134 may be any device capable of accessing network 129including, without limitation, a desktop computer, a laptop computer, orother web-based connectable equipment. More specifically, in theexemplary embodiment, data management system 134 includes a database 136that includes customer data for each of the customers of utility 102. Inthe exemplary embodiment, the customer data may include an enrollmentperiod and/or an enrollment status for each customer for participatingin at least one demand response program. For example, the data mayinclude a selection made by each customer for at least one demandresponse program to participate in. The customer data may also include aparticipation history for each customer. The participation history mayinclude, for example, the previous demand response events that eachcustomer has participated in. The customer data may also include ageographic area of each customer, such as the geographic area where eachcustomer resides. The customer data may include the phase of powerutilized by each customer. The customer data may indicate what type ofcustomer each customer is, such as commercial or residential. Thecustomer data may indicate the types of power consuming devices 112 usedby each customer. The types of devices may include, for example,electric water heater 114, air conditioner 116, pool pump 118, etc.

Moreover, in the exemplary embodiment, data management system 134includes a user interface 138 that receives at least one input from auser, such as an operator and/or employee of utility 102. In theexemplary embodiment, data management system user interface 138 mayinclude, for example, a keyboard, a pointing device, a mouse, a stylus,a touch sensitive panel (e.g., a touch pad or a touch screen), agyroscope, an accelerometer, a position detector, and/or an audio inputinterface (e.g., including a microphone) that enables the user to inputpertinent information.

Data management system 134 may communicate with computing device 106using a wired network connection (e.g., Ethernet or an optical fiber), awireless communication means, such as radio frequency (RF), e.g., FMradio and/or digital audio broadcasting, an Institute of Electrical andElectronics Engineers (IEEE®) 802.11 standard (e.g., 802.11(g) or802.11(n)), the Worldwide Interoperability for Microwave Access (WIMAX®)standard, cellular phone technology (e.g., the Global Standard forMobile communication (GSM)), a satellite communication link, and/or anyother suitable communication means. More specifically, in the exemplaryembodiment, data management system 134 transmits the customer data tocomputing device 106. While the customer data is shown as being storedin database 136 within data management system 134 in the exemplaryembodiment, it should be noted that the customer data may be stored inanother system and/or device. For example, computing device 106 maystore the customer data therein.

FIG. 3 is a block diagram of computing device 106. In the exemplaryembodiment, computing device 106 includes a user interface 204 thatreceives at least one input from a user, such as an employee of utility102 (shown in FIGS. 1 and 2). In the exemplary embodiment, userinterface 204 includes a keyboard 206 that enables the user to inputpertinent information. Alternatively, user interface 204 may include,for example, a pointing device, a mouse, a stylus, a touch sensitivepanel (e.g., a touch pad or a touch screen), a gyroscope, anaccelerometer, a position detector, and/or an audio input interface(e.g., including a microphone).

Moreover, in the exemplary embodiment, computing device 106 includes apresentation interface 207 that presents information, such as inputevents and/or validation results, to the user. In the exemplaryembodiment, presentation interface 207 includes a display adapter 208that is coupled to at least one display device 210. More specifically,in the exemplary embodiment, display device 210 is a visual displaydevice, such as a cathode ray tube (CRT), a liquid crystal display(LCD), an organic LED (OLED) display, and/or an “electronic ink”display. Alternatively, presentation interface 207 may include an audiooutput device (e.g., an audio adapter and/or a speaker) and/or aprinter.

Computing device 106 also includes a processor 214 and a memory device218. In the exemplary embodiment, processor 214 is coupled to userinterface 204, presentation interface 207, and to memory device 218 viaa system bus 220. In the exemplary embodiment, processor 214communicates with the user, such as by prompting the user viapresentation interface 207 and/or by receiving user inputs via userinterface 204. Moreover, in the exemplary embodiment, processor 214 isprogrammed by encoding an operation using one or more executableinstructions and providing the executable instructions in memory device218.

The term “processor” refers generally to any programmable systemincluding systems and microcontrollers, reduced instruction set circuits(RISC), application specific integrated circuits (ASIC), programmablelogic circuits (PLC), and any other circuit or processor capable ofexecuting the functions described herein. The above examples areexemplary only, and thus are not intended to limit in any way thedefinition and/or meaning of the term “processor.”

In the exemplary embodiment, memory device 218 includes one or moredevices that enable information, such as executable instructions and/orother data, to be stored and retrieved. Moreover, in the exemplaryembodiment, memory device 218 includes one or more computer readablemedia, such as, without limitation, dynamic random access memory (DRAM),static random access memory (SRAM), a solid state disk, and/or a harddisk. In the exemplary embodiment, memory device 218 stores, withoutlimitation, application source code, application object code,configuration data, additional input events, application states,assertion statements, validation results, and/or any other type of data.More specifically, in the exemplary embodiment, memory device 218 storesinput data received from a user via user interface 204, and/orinformation received from other components of demand response system 100(shown in FIGS. 1 and 2).

Computing device 106, in the exemplary embodiment, also includes acommunication interface 230 that is coupled to processor 214 via systembus 220. Moreover, in the exemplary embodiment, communication interface230 is communicatively coupled to user notification device 128 vianetwork 129 (shown in FIG. 1). In the exemplary embodiment,communication interface 230 communicates with user notification device128, and/or other components within system 100.

In operation, a user of system 100 (sometimes referred to herein as anoperator) specifies one or more event parameters for a demand responseevent. The user may specify the event parameters via user interface 204,such as, for example, by selecting parameters displayed by presentationinterface 207. The event parameters can include a phase of power, alocation (e.g., a particular node, etc.), an amount of reduction needed,a length of time of a load reduction, a type of customer, one or moretypes of power consuming devices 112, a type of demand response program,etc. The event parameter may be a segregating parameter or a balancingparameter. Thus, for example, the event parameter may be segregation oftypes of power consuming device 112, types of customers, phases ofpower, etc. Alternatively, or additionally, the event parameter may bebalancing of types of power consuming device 112, types of customers,phases of power, etc.

Computing device 106 then creates groups of customers usable to supportthe demand response event based, at least in part, on the eventparameter. To create the groups, computing device 106 identifies thenode at which the demand response event will be called. This node may beidentified by the operator or determined by system computing device 106.Computing device 106 determines which resources (e.g., customers,devices, etc.) may be used to support the demand response event andcreates a pool of customers including the customers potentially useableto support the demand response event. Characteristics of each customerin the pool of customers are retrieved. The characteristics may include,for example, the customer's location, the demand response programs inwhich the customer is enrolled, the phase of power utilized by thecustomer, the power consuming devices 112 used by the customer, the typeof customer (e.g., residential, commercial), and any other suitableinformation. The characteristics may be retrieved by computing device106 from memory device 218, database 136, from user notification device128, etc. Computing device 106 creates groups of customers from the poolof customers based on the retrieved characteristics and the eventparameters.

One or more of the created groups of customers may be used to respond tothe demand response event. The computing device 106 selects one or moreof the created groups and schedules the selected groups. The number ofgroups selected is generally determined by the reduction provided byeach group. The total reduction provided by the selected groups shouldtypically meet or exceed the desired reduction of the demand responseevent. The reduction may be a reduction in, for example, total power, aparticular phase or phases of power, etc. After the groups have beenselected and scheduled for participation in the demand response event,demand response signals are transmitted to the customers (or devices112) in the selected groups. These demand response signals willtypically specify the time, duration, action, etc. for the demandresponse event.

The created groups may be combined to form macrogroups, from which thecomputing device 106 may select and schedule macrogroups forparticipation in the demand response event. For example, groups may becreated, as discussed above, based on an event parameter of device type.If the event parameter is, for example, type of power consuming device,each created group may include a single type of device. Macrogroups maythen be created from the single device groups (sometimes referred to asmicrogroups). The macrogroups may be created based on one or more eventparameter. For example, the macrogroups may be created to balance all ofthe types of power consuming devices in each group. Thus, a macrogroupmay be formed by selecting one microgroup for each of the types ofdevices.

Groups and/or macrogroups may be created before or during the occurrenceof a demand response event. Thus, in some embodiments, microgroups arecreated in advance of any demand response event. Such microgroups may becreated for nodes at which particular demand response events are common.When a demand response event is needed, computing device 106 may quicklycreate macrogroups from the already created microgroups. This may permita quicker response and may be less processor intensive than other knownmethods. Further, groups, whether microgroups or macrogroups, may beassigned group numbers. These group numbers may be transmitted to themembers (i.e., the customers) of the groups and stored, for example, byuser notification device 128. When a demand response signal is to betransmitted to the groups, a single signal, addressed to the groupnumber, may be transmitted for each group, potentially conservingnetwork bandwidth.

Examples of the process of creating groups will now be described withreference to FIG. 2. In the first example, the event parameter issegregation by type of power consuming device 112. The pool of potentialresources are all connected to first lateral line 120. For this example,the operator specifies a group size as a particular number of powerconsuming devices 112. In other examples, the group size may be selectedbased on other parameters, such as total kWh. For the first type ofdevice, electric water heaters 114 for example, the number of groups isdetermined. The total number of the electric water heaters 114 availablein the poletop transformers 124 of first lateral line 120 is determined.This number is divided by the desired group size to get the number ofgroups that will be created. Next, the groups are created. The poletoptransformers 124 are sorted by order of distance on the first lateralline 120, e.g. from left to right in FIG. 2. The first group is createdby assigning the electric water heaters 114 to it in the sequence asfollows: one electric water heater 114 from the furthest poletoptransformer, followed by one from the nearest, then one from the secondfurthest, followed by one from the second nearest and continue to themiddle of the poletop sequence in this manner. This continues until thegroup has been completed to its intended size or the sequence has beencompleted. If the sequence is completed without filling the group to thedesired size, the process starts again at the furthest poletoptransformer and continues (including repeating) until the group has beenfilled to the intended group size. In the process, poletop transformers124 that do not have any additional electric water heaters 114 availableare skipped. After the first group is created in this manner, the nextgroup of electric water heaters 114 is created in the same manner,beginning with the next poletop transformer 124 in the series justcompleted. If the total number of electric water heaters 114 is notevenly divisible by the desired size, the last group may not reach theintended size. After this process has been completed for the devices ofelectric water heaters 114, the process repeats for each additional typeof device, including for example air conditioners 116 and/or pool pumps118.

In another example, the event parameter is balancing by type of powerconsuming device 112. Like the previous example, the pool of potentialresources are all connected to first lateral line 120. The number ofgroups is determined by computing the total number of all powerconsuming devices 112 under first lateral line 120 and dividing it bythe desired group size. Microgroups are then created and segregated bydevice type as described above to create the number of groups determinedin previous steps for each device type. To create a group (ormacrogroup), one microgroup from each device type is selected. This isrepeated to create the remaining groups. As a result, eachgroup/macrogroup will generally include the same number of each type ofdevices. There may be some variation because of unequal numbers ofdevices of different types, numbers of devices not evenly divisible bygroup size, etc.

The process in the previously described examples may be expanded. Forexample, the process may be performed at a feeder or substation level.In such an example, segregated groups may be created by device type foreach of first lateral line 120 and second lateral line 122. Thesemicrogroups may be combined to form larger groups including a singledevice type balanced across first and second lateral lines 120 and 122by alternately selecting one group from first lateral line 120 and onegroup from second lateral line 122. These may further be grouped intolarger groups/macrogroups that are balanced by device type. Because thesubgroups are balanced across the feeders, the resulting macrogroupswill also be balanced across the feeders. As a result, the groups arespread generally evenly across device type and feeder.

The above described process may also be applied to multiple other eventparameters. For example, groups may be created and segregated by two ormore event parameters, such as by device type and phase. These groupsmay then be grouped into larger balanced macrogroups.

FIG. 4 is a flow chart of a method 300 that may be used for providingdemand response events using a computing device, such as computingdevice 106 (shown in FIGS. 1-3). At least one event parameter for ademand response event is received 302. A pool of customers is identified304. The pool of customers includes a plurality of customer potentiallyusable to support the demand response event. Characteristics of eachcustomer in the pool of customers are retrieved 306. A plurality ofgroups of customers is created 308 from the pool of customers based onthe retrieved characteristics and the at least one parameter.

As compared to known demand response systems that are used to enableutilities to manage customers and/or energy consumption by theimplementation of demand response programs, the exemplary apparatus,systems, and methods described herein enable a utility to dynamicallygroup customers for support of a demand response event. Morespecifically, the embodiments described herein provide a computingdevice for use with a demand response system. The computing deviceincludes a memory device for storing customer data of a plurality ofcustomers of a utility. A processor is coupled to the interface andprogrammed to receive at least one event parameter for a demand responseevent. The processor is further programmed to identify a pool ofcustomers from the plurality of customers of the utility and retrievecharacteristics of each customer in the pool of customers. The pool ofcustomers includes a plurality of customers potentially usable tosupport the demand response event. The processor is further programmedto create a plurality of groups of customers from the pool of customersbased on the retrieved characteristics and the at least one eventparameter. By creating groups of customers based on retrievedcharacteristics and at least one event parameter, as opposed toemploying static groups of customers based on demand response programand/or location, the utility is able to target specific customers,locations on their grid, particular power characteristics, etc. toreduce the chances for a failure of the grid, balance power usage amongphases, and/or balance load distribution.

A technical effect of the systems and methods described herein includesat least one of: (a) receiving at least one event parameter for a demandresponse event; (b) identifying a pool of customers; (c) retrievingcharacteristics of each customer in the pool of customers; and (d)creating a plurality of groups of customers from the pool of customersbased on the retrieved characteristics and the at least one parameter.

Exemplary embodiments of the systems and methods are described above indetail. The systems and methods are not limited to the specificembodiments described herein, but rather, components of the systemsand/or steps of the methods may be utilized independently and separatelyfrom other components and/or steps described herein. For example, thesystem may also be used in combination with other apparatus, systems,and methods, and is not limited to practice with only the system asdescribed herein. Rather, the exemplary embodiment can be implementedand utilized in connection with many other applications.

Although specific features of various embodiments of the invention maybe shown in some drawings and not in others, this is for convenienceonly. In accordance with the principles of the invention, any feature ofa drawing may be referenced and/or claimed in combination with anyfeature of any other drawing.

This written description uses examples to disclose the invention,including the best mode, and also to enable any person skilled in theart to practice the invention, including making and using any devices orsystems and performing any incorporated methods. The patentable scope ofthe invention is defined by the claims, and may include other examplesthat occur to those skilled in the art. Such other examples are intendedto be within the scope of the claims if they have structural elementsthat do not differ from the literal language of the claims, or if theyinclude equivalent structural elements with insubstantial differencesfrom the literal language of the claims.

What is claimed is:
 1. A method comprising: receiving at least one eventparameter for a demand response event; identifying a pool of customers,comprising a plurality of customers potentially usable to support thedemand response event; retrieving characteristics of each customer inthe pool of customers; and creating a plurality of groups of customersfrom the pool of customers based on the retrieved characteristics andthe at least one event parameter by: selecting a size of the pluralityof groups; determining a number of groups based on the size and a totalnumber of determined type of power consuming devices of the plurality ofcustomers; and assigning the determined type of power consuming devicesto the plurality of groups based on a distance of the determined type ofpower consuming devices to respective transformers, wherein theretrieved characteristics of each customer at least comprise thedetermined type of power consuming devices.
 2. A method in accordancewith claim 1, further comprising: selecting at least one group ofcustomers from the plurality of groups of customers; and transmitting atleast one demand response signal to the customers in the selected groupof customers.
 3. A method in accordance with claim 1, wherein the atleast one event parameter comprises at least one of a location, a costparameter, an amount of a load reduction, a duration of a loadreduction, and a phase of a load reduction.
 4. A method in accordancewith claim 1, further comprising: storing the created plurality ofgroups of customers; and creating a plurality of macro-groups, eachmacro-group including a plurality of groups selected from the storedplurality of groups.
 5. A method in accordance with claim 4, furthercomprising selecting at least one macro-group from the plurality ofmacro-groups; and transmitting at least one demand response signal tothe customers in the selected macro-group.
 6. A method in accordancewith claim 5, wherein said creating a plurality of groups of customersfrom the pool of customers based on the retrieved characteristics andthe at least one parameter is performed prior to an occurrence of ademand response event, and wherein said creating a plurality ofmacro-groups is performed during the occurrence of the demand responseevent.
 7. A method in accordance with claim 1, wherein the customers inthe pool of customers consume a plurality of different phases of power,and wherein said creating a plurality of groups of customers from thepool of customers based on the retrieved characteristics and the atleast one parameter comprises creating a plurality of groups each havingabout a same number of customers consuming each phase of power.
 8. Amethod in accordance with claim 1, wherein the pool of customerscomprises a plurality of different types of customer, and wherein saidcreating a plurality of groups of customers from the pool of customersbased on the retrieved characteristics and the at least one parametercomprises creating a plurality of groups each having about a same numberof each type of customer.
 9. A computing device for use with a demandresponse system, said computing device comprising: a memory device forstoring customer data of a plurality of customers of a utility; and aprocessor coupled to said memory device and programmed to: receive atleast one event parameter for a demand response event; identify a poolof customers from the plurality of customers of the utility, the pool ofcustomers comprising a plurality of customers potentially usable tosupport the demand response event; retrieve characteristics of eachcustomer in the pool of customers; and create a plurality of groups ofcustomers from the pool of customers based on the retrievedcharacteristics and the at least one parameter by: selecting a size ofthe plurality of groups; determining a number of groups based on thesize and a total number of determined type of power consuming devices ofthe plurality of customers; and assigning the determined type of powerconsuming devices to the plurality of groups based on a distance of thedetermined type of power consuming devices to respective transformers,wherein the retrieved characteristics of each customer at least comprisethe determined type of power consuming devices.
 10. A computing devicein accordance with claim 9, wherein the at least one event parameterincludes at least one of a location, a cost parameter, an amount of aload reduction, a duration of a load reduction, and a phase of a loadreduction.
 11. A computing device in accordance with claim 9, whereinsaid processor is further programmed to: select at least one group ofcustomers from the plurality of groups of customers; and transmit atleast one demand response signal to the customers in the selected groupof customers.
 12. A computing device in accordance with claim 9, whereinsaid processor is further programmed to: store the created plurality ofgroups of customers to said memory device; and create a plurality ofmacro-groups, each macro-group including a plurality of groups selectedfrom the stored plurality of groups.
 13. A computing device inaccordance with claim 12, wherein said processor is further programmedto: select at least one macro-group from the plurality of macro-groups;and transmit at least one demand response signal to the customers in theselected macro-group.
 14. A computing device in accordance with claim12, wherein customers in the pool of customers consume power in aplurality of different phases, customers in the pool of customers have aplurality of different types of power consuming devices, and the pool ofcustomers comprises a plurality of types of customer, and wherein saidprocessor is further programmed to create the plurality of groups ofcustomers from the pool of customers such that at least one of: eachgroup has about a same amount of each type of power consuming device;each group has about a same number of customers consuming each phase ofpower; and each group has about a same number of each type of customer.15. A demand response system comprising: a computing device comprising:a memory device for storing customer data of a plurality of customers ofa utility; and a processor coupled to said memory device and programmedto: receive at least one event parameter for a demand response event;identify a pool of customers from the plurality of customers of theutility, the pool of customers comprising a plurality of customerspotentially usable to support the demand response event; retrievecharacteristics of each customer in the pool of customers; and create aplurality of groups of customers from the pool of customers based on theretrieved characteristics and the at least one parameter by: selecting asize of the plurality of groups; determining a number of groups based onthe size and a total number of determined type of power consumingdevices of the plurality of customers; and assigning the determined typeof power consuming devices to the plurality of groups based on adistance of the determined type of power consuming devices to respectivetransformers, wherein the retrieved characteristics of each customer atleast comprise the determined type of power consuming devices.
 16. Ademand response system in accordance with claim 15, wherein the at leastone event parameter includes at least one of a location, a costparameter, an amount of a load reduction, a duration of a loadreduction, and a phase of a load reduction.
 17. A demand response systemin accordance with claim 15, wherein the processor is further programmedto: select at least one group of customers from the plurality of groupsof customers; and transmit at least one demand response signal to thecustomers in the selected group of customers.
 18. A demand responsesystem in accordance with claim 15, wherein said processor is furtherprogrammed to: store the created plurality of groups of customers to thememory device; and create a plurality of macro-groups, each macro-groupincluding a plurality of groups selected from the stored plurality ofgroups.
 19. A demand response system in accordance with claim 18,wherein the processor is further programmed to: select at least onemacro-group from the plurality of macro-groups; and transmit at leastone demand response signal to the customers in the selected macro-group.